Re: Fatal problem with numpy 1.6.x and the disp_spin_speed branch changes. -- July 25, 2014 - 14:48

Hi,

Rather than downgrading, on a Linux system or Mac (with Xcode) it is
probably easier to make a local install of Python.  For Python, as a
user run:

$ ./configure --prefix=~/python/numpy-1.6_testing
$ make
$ make install

Then install a numpy 1.6 version with:

$ ~/python/numpy-1.6_testing/bin/python setup.py install

You'll probably need to get minfx and bmrblib as well
(https://gna.org/projects/minfx/, https://gna.org/projects/bmrblib/).
Then you'll have a testing Python version installed in
~/python/numpy-1.6_testing.  I have this for multiple Python and numpy
versions for testing purposes:

$ ls -1 /data/python/bin/python[0-9].[0-9]
/data/python/bin/python1.0*
/data/python/bin/python1.2*
/data/python/bin/python1.3*
/data/python/bin/python1.4*
/data/python/bin/python1.5*
/data/python/bin/python1.6*
/data/python/bin/python2.0*
/data/python/bin/python2.1*
/data/python/bin/python2.2*
/data/python/bin/python2.3*
/data/python/bin/python2.4*
/data/python/bin/python2.5*
/data/python/bin/python2.6*
/data/python/bin/python2.7*
/data/python/bin/python3.0*
/data/python/bin/python3.1*
/data/python/bin/python3.2*
/data/python/bin/python3.3*
/data/python/bin/python3.4*

Regards,

Edward


On 25 July 2014 14:34, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> wrote:
> Hi Edward.
>
> I would suggest an implementation of striding through the data.
>
> The necessary functions for this implementation is already present in
> lib/dispersion matrix_exponential.py and matrix_power.py.
>
> I will look into this later.
>
> I will try to see, if I can do a local downgrade of numpy to 1.6, to
> check it is working.
>
> Best
> Troels
>
>
> 2014-07-25 14:09 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:
> > Hi Troels,
> >
> > We have a major problem in trunk caused by the recent merger of the
> > disp_spin_speed branch.  When I run the Relax_disp system tests, the
> > unit tests, or the Relax_disp GUI tests, I see many, many failures due
> > to problems with the numpy.linalg.eig() function on numpy 1.6.1,
> > 1.6.2, and 1.7.0.  The error for one of the unit tests is:
> >
> > ======================================================================
> > ERROR: Test the r2eff_ns_cpmg_2site_3D() function for no exchange when dw 
> > = 0.0.
> > ----------------------------------------------------------------------
> > Traceback (most recent call last):
> >   File 
> > "/data/relax/relax-trunk/test_suite/unit_tests/_lib/_dispersion/test_ns_cpmg_2site_3d.py",
> > line 130, in test_ns_cpmg_2site_3D_no_rex1
> >     self.calc_r2eff()
> >   File 
> > "/data/relax/relax-trunk/test_suite/unit_tests/_lib/_dispersion/test_ns_cpmg_2site_3d.py",
> > line 79, in calc_r2eff
> >     r2eff_ns_cpmg_2site_3D(r180x=self.r180x, M0=self.M0,
> > M0_T=self.M0_T, r20a=self.r20a*a, r20b=self.r20b*a, pA=self.pA,
> > dw=dw_frq*a, dw_orig=dw_frq*a, kex=self.kex,
> > inv_tcpmg=self.inv_relax_times*a, tcp=self.tau_cpmg*a,
> > back_calc=self.R2eff, num_points=self.num_points*b, power=self.ncyc*a)
> >   File "/data/relax/relax-trunk/lib/dispersion/ns_cpmg_2site_3d.py",
> > line 299, in r2eff_ns_cpmg_2site_3D
> >     Rexpo_mat = matrix_exponential_rank_NE_NS_NM_NO_ND_x_x(R_mat)
> >   File "/data/relax/relax-trunk/lib/dispersion/matrix_exponential.py",
> > line 78, in matrix_exponential_rank_NE_NS_NM_NO_ND_x_x
> >     W, V = eig(A)
> >   File "/data/python/lib/python2.5/site-packages/numpy/linalg/linalg.py",
> > line 1015, in eig
> >     _assertRank2(a)
> >   File "/data/python/lib/python2.5/site-packages/numpy/linalg/linalg.py",
> > line 155, in _assertRank2
> >     two-dimensional' % len(a.shape)
> > LinAlgError: 7-dimensional array given. Array must be
> > two-dimensional
> >
> > ----------------------------------------------------------------------
> >
> > Here are the API differences between numpy versions:
> >
> > 1.8.1:  
> > http://docs.scipy.org/doc/numpy-1.8.1/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
> > 1.8.0:  
> > http://docs.scipy.org/doc/numpy-1.8.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
> > 1.7.0:  
> > http://docs.scipy.org/doc/numpy-1.7.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
> > 1.6.0:  
> > http://docs.scipy.org/doc/numpy-1.6.0/reference/generated/numpy.linalg.eig.html#numpy.linalg.eig
> >
> > You can see that the input changes from (M, M) to (..., M, M) between
> > 1.7.0 and 1.8.0.  We cannot require numpy >= 1.8 as many current
> > distributions have not shifted to this version yet.  Most sys admins
> > would kill me for even suggesting that ;)  Therefore we need to come
> > up with a solution and quickly.
> >
> > The best would be to add an eig() function to the lib.compat module.
> > For numpy >= 1.8.0 it will use the numpy.linalg.eig() function.  For
> > the other versions, we need an alternative solution.  Maybe using slow
> > Python looping over the higher dimensions would be ok.
> >
> > I will not report this as a bug, as no released relax versions are 
> > affected.
> >
> > Cheers,
> >
> > Edward
> >
> > _______________________________________________
> > relax (http://www.nmr-relax.com)
> >
> > This is the relax-devel mailing list
> > relax-devel@xxxxxxx
> >
> > To unsubscribe from this list, get a password
> > reminder, or change your subscription options,
> > visit the list information page at
> > https://mail.gna.org/listinfo/relax-devel